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Ammar Peter Kaka
Researcher at Heriot-Watt University
Publications - 78
Citations - 1456
Ammar Peter Kaka is an academic researcher from Heriot-Watt University. The author has contributed to research in topics: Cash flow & Cash flow forecasting. The author has an hindex of 21, co-authored 78 publications receiving 1339 citations. Previous affiliations of Ammar Peter Kaka include University of Edinburgh & Bond University.
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Towards automated progress assessment of workpackage components in construction projects using computer vision
TL;DR: A system that employs computer vision techniques to report on the progress of these work packages automatically by analysing sequences of digital images acquired regularly by on-site cameras is proposed, allowing a project to be monitored more effectively.
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Automating progress measurement of construction projects
Xiaonan Zhang,N Bakis,T.C. Lukins,Yahaya Makarfi Ibrahim,Song Wu,Mike Kagioglou,Ghassan Aouad,Ammar Peter Kaka,Emanuele Trucco +8 more
TL;DR: In this article, an integrated building information system that aims to determine the progress of construction from digital images captured on site in order to semi-automate the work in progress measurement and calculation of interim payments as well as function as an early warning system of potential delays.
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A neural networks approach for cost flow forecasting
A H Boussabaine,Ammar Peter Kaka +1 more
TL;DR: The feasibility of using neural networks for predicting the cost flow of construction projects is investigated, the need for cost flow forecasting is explained, and neural networks are introduced as an alternative approach to those mathematical and statistical methods.
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An evaluation of risk factors impacting construction cash flow forecast
TL;DR: In this article, the extent of occurrence and impact of risk factors responsible for the variation between the forecast and actual construction cash flow was assessed through a structured questionnaire administered to UK contracting organizations.
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Modelling standard cost commitment curves for contractors' cash flow forecasting
TL;DR: In this article, the authors identify causes behind the inaccuracy of current standard value S-curves and propose the use of standard cost commitment models to forecast cash flow with reasonable accuracy.